title: Estimating the glomerular filtration rate in the general population using different equations: effects on classification and association.
abstract: OBJECTIVE
  Several formulas for glomerular filtration rate (GFR) estimation, based on serum creatinine or cystatin C, have been proposed. We assessed the impact of some of these equations on estimated GFR (eGFR) and chronic kidney disease (CKD) prevalence, and on the association with cardiovascular risk factors, in a general population sample characterized by a young mean age.
  
  
  METHODS
  We studied 1,199 individuals from three Alpine villages enrolled into the MICROS study. eGFR was obtained with the 4- and 6-parameter MDRD study equations, the Virga equation, and with the three CKD-EPI formulas for creatinine, cystatin C, and the combination of creatinine and cystatin C. We assessed the concordance between quantitative eGFR levels, CKD prevalence, and in terms of association with total, LDL, and HDL cholesterol.
  
  
  RESULTS
  The highest and lowest eGFR levels corresponded to the cystatin C-based and MDRD-4 equations, respectively. CKD prevalence varied from 1.8% (Virga) to 5.8% (MDRD-4). The CKD-EPI based on creatinine showed the highest agreement with all other equations. Agreement between methods was higher at lower eGFR levels, older age, and in the presence of diabetes and hypertension. Creatinine-based estimates of eGFR were associated with total and low-density lipoprotein but not high-density lipoprotein cholesterol. The opposite was observed for the cystatin C-based GFR.
  
  
  CONCLUSIONS
  GFR estimation is strongly affected by the chosen equation. Differences are more pronounced in healthy and younger individuals. To identify CKD risk factors, the choice of the equation is of secondary importance to the choice of the biomarker used in the formula. If eGFR is not calibrated to a gold standard GFR in the general population, reports about CKD prevalence should be considered with caution.
authors.affiliation: Center for Biomedicine, European Academy of Bolzano/Bozen (EURAC), Bolzano, Italy. cristian.pattaro@eurac.edu
authors.forename: Cristian
authors.initials: C
authors.lastname: Pattaro
authors.forename: Peter
authors.initials: P
authors.lastname: Riegler
authors.forename: Gerald
authors.initials: G
authors.lastname: Stifter
authors.forename: Mirko
authors.initials: M
authors.lastname: Modenese
authors.forename: Cosetta
authors.initials: C
authors.lastname: Minelli
authors.forename: Peter P
authors.initials: PP
authors.lastname: Pramstaller
mesh_terms: D000465:Algorithms; D001317:Austria / Q000453:epidemiology; D003404:Creatinine / Q000097:blood*; D055316:Cystatin C / Q000097:blood*; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D005260:Female; D005919:Glomerular Filtration Rate; D006801:Humans; D007558:Italy / Q000453:epidemiology; D007674:Kidney Diseases / Q000175:diagnosis* / Q000453:epidemiology*; D007677:Kidney Function Tests / Q000379:methods*; D008297:Male; D008875:Middle Aged; D015995:Prevalence; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013557:Switzerland / Q000453:epidemiology
chemical_list: D055316:Cystatin C; D003404:Creatinine